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GWAS Study

Genome-Wide Association Study of Alzheimer's Disease Brain Imaging Biomarkers and Neuropsychological Phenotypes in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Dataset.

Homann J, Osburg T, Ohlei O et al.

35386118 PubMed ID
GWAS Study Type
402 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

HJ
Homann J
OT
Osburg T
OO
Ohlei O
DV
Dobricic V
DL
Deecke L
BI
Bos I
VR
Vandenberghe R
GS
Gabel S
SP
Scheltens P
TC
Teunissen CE
ES
Engelborghs S
FG
Frisoni G
BO
Blin O
RJ
Richardson JC
BR
Bordet R
LA
Lleó A
AD
Alcolea D
PJ
Popp J
CC
Clark C
PG
Peyratout G
MP
Martinez-Lage P
TM
Tainta M
DR
Dobson RJB
LC
Legido-Quigley C
SK
Sleegers K
VB
Van Broeckhoven C
WM
Wittig M
FA
Franke A
LC
Lill CM
BK
Blennow K
ZH
Zetterberg H
LS
Lovestone S
SJ
Streffer J
TK
Ten Kate M
VS
Vos SJB
BF
Barkhof F
VP
Visser PJ
BL
Bertram L
Chapter II

Abstract

Summary of the research findings

Alzheimer's disease (AD) is the most frequent neurodegenerative disease with an increasing prevalence in industrialized, aging populations. AD susceptibility has an established genetic basis which has been the focus of a large number of genome-wide association studies (GWAS) published over the last decade. Most of these GWAS used dichotomized clinical diagnostic status, i.e., case vs. control classification, as outcome phenotypes, without the use of biomarkers. An alternative and potentially more powerful study design is afforded by using quantitative AD-related phenotypes as GWAS outcome traits, an analysis paradigm that we followed in this work. Specifically, we utilized genotype and phenotype data from n = 931 individuals collected under the auspices of the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study to perform a total of 19 separate GWAS analyses. As outcomes we used five magnetic resonance imaging (MRI) traits and seven cognitive performance traits. For the latter, longitudinal data from at least two timepoints were available in addition to cross-sectional assessments at baseline. Our GWAS analyses revealed several genome-wide significant associations for the neuropsychological performance measures, in particular those assayed longitudinally. Among the most noteworthy signals were associations in or near EHBP1 (EH domain binding protein 1; on chromosome 2p15) and CEP112 (centrosomal protein 112; 17q24.1) with delayed recall as well as SMOC2 (SPARC related modular calcium binding 2; 6p27) with immediate recall in a memory performance test. On the X chromosome, which is often excluded in other GWAS, we identified a genome-wide significant signal near IL1RAPL1 (interleukin 1 receptor accessory protein like 1; Xp21.3). While polygenic score (PGS) analyses showed the expected strong associations with SNPs highlighted in relevant previous GWAS on hippocampal volume and cognitive function, they did not show noteworthy associations with recent AD risk GWAS findings. In summary, our study highlights the power of using quantitative endophenotypes as outcome traits in AD-related GWAS analyses and nominates several new loci not previously implicated in cognitive decline.

402 European ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

402
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Chapter IV

Analysis

Comprehensive review of health and genetic findings

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